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Testing the Validity and Reliability of Intrinsic Motivation Inventory Subscales Within ASSISTments

  • Korinn S. Ostrow
  • Neil T. Heffernan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10947)

Abstract

Online learning environments allow for the implementation of psychometric scales on diverse samples of students participating in authentic learning tasks. One such scale, the Intrinsic Motivation Inventory (IMI) can be used to inform stakeholders of students’ subjective motivational and regulatory styles. The IMI is a multidimensional scale developed in support of Self-Determination Theory [1, 2, 3], a strongly validated theory stating that motivation and regulation are moderated by three innate needs: autonomy, belonging, and competence. As applied to education, the theory posits that students who perceive volition in a task, those who report stronger connections with peers and teachers, and those who perceive themselves as competent in a task are more likely to internalize the task and excel. ASSISTments, an online mathematics platform, is hosting a series of randomized controlled trials targeting these needs to promote integrated learning. The present work supports these studies by attempting to validate four subscales of the IMI within ASSISTments. Iterative factor analysis and item reduction techniques are used to optimize the reliability of these subscales and limit the obtrusive nature of future data collection efforts. Such scale validation efforts are valuable because student perceptions can serve as powerful covariates in differentiating effective learning interventions.

Keywords

Intrinsic Motivation Inventory Self-Determination Theory ASSISTments Factor analysis Validity Reliability 

Notes

Acknowledgments

We acknowledge funding from NSF grants (ACI-1440753, DRL-1252297, DRL-1109483, DRL-1316736, DGE-1535428, OAC-1724889, OAC-1636782 & DRL-1031398), the U.S. Department of Education (IES R305A120125 & R305C100024 and GAANN), the ONR, and the Gates Foundation. Thanks to S.O. & L.P.B.O.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Worcester Polytechnic InstituteWorcesterUSA

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